Simulating A/B tests with data.table
A set of function simulate A/B tests that span multiple weeks using data.table
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Data Scientist at Sky Betting & Gaming, Leeds, UK. Interested in all things data science.
Adjusting for covariates and baseline differences in A/B testing
This post will focus on an issue commonly faced when analysing A/B tests – dealing with baselines differences between the treatment and control groups
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Approximate Nearest Neighbours in R and Spark
An exploration of Local Sensitivity Hashing, a technique for approximating nearest neighbours, with sparklyr and R
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Feature selection by cross-validation with sparklyr
Cross-validation provides a simple and direct method for feature selection. This post runs through how to do it with sparkylyr
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Cross-validation with sparklyr 2: Electric Boogaloo
Revisiting cross-validation with sparklyr making use of new in-build functions
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SparkR vs sparklyr for interacting with Spark from R
Comparing SparkR and sparklyr, two R APIs to Spark
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Machine learning and k-fold cross validation with sparklyr
An introduction to machine learning and cross-validation with sparklyr
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Writing your thesis with bookdown
This post details some tips and tricks for writing a thesis/dissertation using the bookdown R package by Yihui Xie
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Intro to R slides
For the Perception Action and Cognition Lab Open Science Week, 2017 (University of Leeds) I gave two talks introducing R. You can see the slides below. The code for the slides can be found over at GitHub.
An introduction to R In this introduction to R I focused on tools from the tidyverse, as well as trying to provide some motivation for learning R. The audience was academics and postgraduates in a psychology department.
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Modelling working memory precision in R
Functions for modelling continuous response working memory tasks
I have translated Paul Bays’ Matlab functions for modeling continuous response data into R . Bays’ guide to the Matlab functions and their usage can be found here. I have a detailed guide to the R functions and their usage over on Github.
A typical precision task has participants recall a feature of stimulus on a continuous scale rather than using classic correct/incorrect scoring. The model described in Bayes et al.
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